Meet PhD candidate Emily Sheng, who is researching how
natural language processing could revolutionize how knowledge is
accessed in scientific literature.

Where are you from and what were you doing
before your enrolled in your PhD?

I’m originally from northern California and completed
my undergraduate in cognitive science and computer science at
the University of California, Berkeley. Initially, I was studying
biology, but I decided to switch to cognitive science because I
was particularly interested in the brain and language. After
graduation, I worked for a startup in voice search technology for
a year, before deciding to go back to research.

How did you find out about the program and why
did you choose ISI?

I knew I wanted to pursue research in natural language
processing and was looking for a potential advisor in that area
when I found professor Prem
Natarajan on the ISI website. When I met with him, he
seemed very invested in growing this area of research at ISI. I
also talked to some people he had previously worked with, which
was encouraging. I applied through the Viterbi School of
Engineering PhD application process and selected professor
Natarajan as my advisor.

As an off-campus institute, I felt ISI would offer a different
kind of PhD experience—it seemed like there would be
space to grow and work alongside not only my peers, but also
postdoc researchers and other experienced staff in my lab.

What’s the best thing about being a PhD
student at ISI?

You have the freedom to explore whatever research area
really interests you. You can also choose whether you want to
make your experience more hands-on or theoretical. Most of the
people in my lab are conducting hands-on application-based
research, working on a range of topics, including computer
vision, recommendation systems, and natural language
processing. Even just within professor Natarajan’s
research group, people are working on many diverse research
topics, so you get exposure to people from a large variety of
backgrounds.

What is your area of emphasis and how do you
intend to apply this in your future career?

Very broadly, I work on research problems in natural
language processing; more specifically, tasks related to
organizing knowledge in scientific literature to better facilitate
access to that knowledge. For example, I work on different types
of information extraction problems, including named entity
recognition. After I finish my PhD, I’m interested in
working in industry. I’ve already worked at a startup, so
I’d like to gain experience at a large company during my
PhD internship this summer.

What advice would you give to other students
embarking on PhD research at ISI?

Don’t be afraid to ask for guidance. I can always go
to people when I have questions, even if they’re in one of
the other ISI research offices—people are always willing to
help or take the time to walk you through a concept.